projectTracks {track2KBA} | R Documentation |
Project tracking data
Description
projectTracks
is a convenience function to project tracking data to a
an equal-area projection for use in kernel density analysis.
Usage
projectTracks(dataGroup, projType, custom)
Arguments
dataGroup |
data.frame or SpatialPointsDataFrame. Tracking data, with
fields as named by |
projType |
character. Select type of equal-area projection to use. Two options are are available: 'cylin' projects to a World Cylindrical Equal Area projection, and 'azim' projects to a Lambert Azimuthal EA. |
custom |
logical (TRUE/FALSE). Choose whether projection will use default centering parameters or whether to set projection center on centroid of latitude and longitude in dataGroup. Input data can be tracks split into trips (i.e. output of
|
Details
Data are transformed to either a World Cylindrical Equal Area, or a Lambert
equal-area projection. Cylindrical projections generally appear better for
data that are distributed more along one axis, while azimuthal appear better
for data that is distributed evenly within a radius. The most important thing
is that the data are in an equal-area projection for Kernel Density Analysis
(e.g. estSpaceUse
).
If custom=TRUE
, the projection will be centered on the data. This
is particularly preferable for data that cross the international dateline,
or near the poles. However, it is important to recognize that this projection
is specific to inpute dataset (i.e. dataGroup
) so if
projectTracks
is run again with even slightly different data, the
projections will differ, which may cause issues down the line if merging
spatial datasets again.
NOTE that these projections may not be the most appropriate for your data and
it is almost certainly better to manually identify a projection appropriate
for your study region. Custom projections are centered on the centroid of
the tracking locations, which is biased for locations close to the poles. In
this case it would be better identify an appropriate polar projection for
your study are instead of relying on projectTracks
. So it is not
strictly necessary for projectTracks
to be used in track2KBA analysis,
what is important is that an equal-area projection of some kind is used when
constructing utilization distributions.
Value
Returns a SpatialPointsDataFrame, which can be used for the following
functions: findScale
, estSpaceUse
,
indEffectTest
, repAssess
See Also
Examples
dataGroup <- data.frame(Longitude = c(1, 2, 3, 1),
Latitude = c(1, 1, 2, 1),
ID = rep("A", 4),
DateTime = format(
lubridate::ymd_hms("2021-01-01 00:00:00") +
lubridate::hours(0:3)
)
)
## project tracks
tracks_prj <- projectTracks(
dataGroup,
projType = "azim",
custom = "TRUE"
)